ABSTRACT
Sound sensing is one of the low-hanging fruits of smart city applications. Technically, it is relatively easy to accomplish: measuring loudness is computationally cheap, transmitting the results requires low bandwidths and the minimum hardware specifications are relatively modest. Noise sensing is considered a solved problem by most urban engineers; a black-boxed solution just waiting to be deployed. Approaches to measurement and categorization are never just technicalities, they embody a perspective on the world. They give shape to different assumptions about what the problem is, how it should be measured, and what consequences might arise as a result of the measurement. The quantification of noise emissions follows a number of conventions informed by findings from physics, acoustics, human medicine, and psychology. The metric had to be both “objective” and easily implementable. Concerns about privacy and surveillance are among the most discussed issues pertaining to smart cities.
